Deconvolve_transcriptome: Deconvolve_transcriptome

Description Usage Arguments Value Examples

View source: R/Deconvolve_transcriptome.R

Description

Deconvolve_transcriptome measures the similarity of one or many query RNA-seq or microarray samples to samples with known differentiation stage contained in the training models.

Usage

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Deconvolve_transcriptome(
    transcriptome_data,
    deconvolution_algorithm,
    models,
    nr_permutations,
    output_file
)

Arguments

transcriptome_data

A data frame that contains the gene expression data. Rows are expected to be HGNC symbols and columns are expected to contain the samples.

deconvolution_algorithm

Which deconvolution algorithm to choose from. Options: 'music','bseqsc' (CIBERSORT), 'nmf'.

models

List of models to be used. Use show_models_NMF(), show_models_music() or show_models_bseqsc() to view available models or add new model via add_deconvolution_training_model_*().

nr_permutations

Utilized to calculate p-value Higher amount of permutations generally lead to more precise p-value estimates. Default value 1000.

output_file

Path of output file. If not specified, no hard-disk written output will occur.

Value

Similarity measurements of differentiation stages.

Examples

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data("visualization_data")
Deconvolve_transcriptome(
    transcriptome_data = visualization_data
)

RaikOtto/artdeco documentation built on Nov. 3, 2021, 6:18 p.m.